InfoQ Homepage Cloud Computing Content on InfoQ
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Day Two Kubernetes: Tools for Operability
Bridget Kromhout discusses what containers and Kubernetes clusters are at a high level, and looks into the practical application of open source tools to simplify cluster management.
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Building Data Environments for Production Microservices with Geode
Ryan Hunt discusses HCSC’s approach to support rapid development and continuous deployment of a high-performance data environment that backs their Digital APIs.
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Designing Automated Pipelines for Unseen Custom Data
Kevin Moore discusses some challenges in designing automated machine learning pipelines that can deal with custom user data that it has never seen before, as well as some of Salesforce’s solutions.
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Building Responsive Systems with Serverless, Event-Driven Java
Asir Selvasingh, Richard Seroter discuss building a responsive Java system using an even-driven architecture with Boot, Event Hubs, Cosmos DB, App Service, PCF, Functions and Spring Cloud Functions.
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Serverless and Chatbots: A Match Made in the Cloud
Gillian Armstrong uses practical examples from their chatbot and shares some of the lessons they learned which help starting a chatbot.
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Extreme Pipelines
Cory Jett, William Marchlewski discuss how Mastercard built a CF pipeline, the current state, and what the future holds for automation.
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Containers - What Are They Good For?
Jimmy Bogard takes a look at containerizing all aspects of a developer's toolkit, from local dependencies, development, build, test, and finally, production, to see where containers fit.
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Expect the Unexpected: How to Handle Errors Gracefully
Bastian Hoffman discusses monitoring and logging errors, showing how to handle them, covering deployment strategies with circuit breakers, and reducing functionality to minimize impact.
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Going Cloud Native with Spring Cloud Azure
Yitao Dong and Yawei Wang show how to create cloud native apps with Spring Cloud on Azure.
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Accelerated Spark on Azure: Seamless and Scalable Hardware Offloads in the Cloud
Yuval Degani shows how hardware accelerations in Azure can be utilized to speed-up Spark jobs, with the aid of RDMA (Remote Direct Memory Access) support in the VM.
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Implementing AutoML Techniques at Salesforce Scale
Matthew Tovbin shows how to build ML models using AutoML (Salesforce), including techniques for automatic data processing, feature generation, model selection, hyperparameter tuning and evaluation.
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Look Ma, No Servers: AWS Serverless Applications with the .NET Stack
Bryan Slatner discusses the need to think differently about serverless applications and demonstrates creating and deploying an entire web app without any servers, focusing on AWS and .NET.
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